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You can do this either by using the label= keyword in each of your plt.plot() calls or by assigning your labels as a tuple or list within legend, as in this working example:
1 sie 2024 · Below are some examples that can see the Matplotlib interactive mode setup using Matplotlib.pyplot.legend () in Python: Add a Legend to a Matplotlib. In this example, a simple quadratic function \ ( y = x^2 \) is plotted against the x-values [1, 2, 3, 4, 5]. A legend labeled “single element” is added to the plot, clarifying the plotted data. Python
For example: ax.plot( [1,2,3])ax.plot( [5,6,7])ax.legend( ['First line','Second line']) Parameters: handleslist of (Artist or tuple of Artist), optional. A list of Artists (lines, patches) to be added to the legend.
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Go to the end to download the full example code. Legend guide #. This legend guide extends the legend docstring - please read it before proceeding with this guide. This guide makes use of some common terms, which are documented here for clarity: legend entry #. A legend is made up of one or more legend entries.
Understanding how to position legends, whether inside or outside a chart, can enhance data interpretation. This article offers a comprehensive guide on leveraging the legend() function in matplotlib for enhancing your data visualizations.
Matplotlib legend is an essential component of data visualization in Python. When creating plots with multiple data series, a legend helps viewers understand what each line, marker, or color represents.
